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Supervised learning

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MLOps: What is MLOps

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DeepLearning: neural network

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NLP: What is NLP

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PyTorch: What is PyTorch

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ComputerVision: what is cv

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TensorFlow: what is tf

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Unsupervised learning

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MLOps: goal

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DeepLearning: neuron

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NLP: token

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PyTorch: tensor

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ComputerVision: pixel

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TensorFlow: tensor tf

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Classification vs regression

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MLOps: reproducibility

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DeepLearning: activation

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NLP: corpus

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PyTorch: tensor def

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ComputerVision: channels

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TensorFlow: keras

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Regression target

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MLOps: experiment tracking

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DeepLearning: relu

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NLP: vocabulary

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PyTorch: gpu tensor

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ComputerVision: grayscale

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TensorFlow: sequential

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Overfitting

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MLOps: model registry

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DeepLearning: sigmoid

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NLP: stopwords

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PyTorch: autograd

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ComputerVision: resolution

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TensorFlow: dense

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Underfitting

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MLOps: data versioning

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DeepLearning: softmax

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NLP: stemming

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PyTorch: requires_grad

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ComputerVision: classification

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TensorFlow: conv2d tf

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Train/test split

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MLOps: feature store

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DeepLearning: forward pass

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NLP: lemmatization

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PyTorch: backward

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ComputerVision: detection

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TensorFlow: activation tf

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Cross validation

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MLOps: train-serve skew

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DeepLearning: loss

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NLP: n-gram

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PyTorch: optimizer step

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ComputerVision: segmentation

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TensorFlow: compile

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Bias-variance

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MLOps: CI for ML

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DeepLearning: backprop

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NLP: bag of words

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